Identifying Fatigue Indicators Using Gait Variability Measures: A Longitudinal Study on Elderly Brisk Walking
Real-time detection of fatigue in the elderly during physical exercises can help identify the stability and thus falling risks which are commonly achieved by the investigation of kinematic parameters. In this study, we aimed to identify the change in gait variability parameters from inertial measure...
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MDPI AG
2020-12-01
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| Online Access: | https://www.mdpi.com/1424-8220/20/23/6983 |
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| author | Guoxin Zhang Ivy Kwan-Kei Wong Tony Lin-Wei Chen Tommy Tung-Ho Hong Duo Wai-Chi Wong Yinghu Peng Fei Yan Yan Wang Qitao Tan Ming Zhang |
| author_facet | Guoxin Zhang Ivy Kwan-Kei Wong Tony Lin-Wei Chen Tommy Tung-Ho Hong Duo Wai-Chi Wong Yinghu Peng Fei Yan Yan Wang Qitao Tan Ming Zhang |
| author_sort | Guoxin Zhang |
| collection | DOAJ |
| description | Real-time detection of fatigue in the elderly during physical exercises can help identify the stability and thus falling risks which are commonly achieved by the investigation of kinematic parameters. In this study, we aimed to identify the change in gait variability parameters from inertial measurement units (IMU) during a course of 60 min brisk walking which could lay the foundation for the development of fatigue-detecting wearable sensors. Eighteen elderly people were invited to participate in the brisk walking trials for 60 min with a single IMU attached to the posterior heel region of the dominant side. Nine sets of signals, including the accelerations, angular velocities, and rotation angles of the heel in three anatomical axes, were measured and extracted at the three walking times (baseline, 30th min, and 60th min) of the trial for analysis. Sixteen of eighteen participants reported fatigue after walking, and there were significant differences in the median acceleration (<i>p</i> = 0.001), variability of angular velocity (<i>p</i> = 0.025), and range of angle rotation (<i>p</i> = 0.0011), in the medial–lateral direction. In addition, there were also significant differences in the heel pronation angle (<i>p</i> = 0.005) and variability and energy consumption of the angles in the anterior–posterior axis (<i>p</i> = 0.028, <i>p</i> = 0.028), medial–lateral axis (<i>p</i> = 0.014, <i>p</i> = 0.014), and vertical axis (<i>p</i> = 0.002, <i>p</i> < 0.001). Our study demonstrated that a single IMU on the posterior heel of the dominant side can address the variability of kinematics parameters for elderly performing prolonged brisk walking and could serve as an indicator for walking instability, and thus fatigue. |
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| spelling | doaj.art-1287074a7a8f44fd91bfac3b1dfa28f72023-11-20T23:43:54ZengMDPI AGSensors1424-82202020-12-012023698310.3390/s20236983Identifying Fatigue Indicators Using Gait Variability Measures: A Longitudinal Study on Elderly Brisk WalkingGuoxin Zhang0Ivy Kwan-Kei Wong1Tony Lin-Wei Chen2Tommy Tung-Ho Hong3Duo Wai-Chi Wong4Yinghu Peng5Fei Yan6Yan Wang7Qitao Tan8Ming Zhang9Department of Biomedical Engineering, The Hong Kong Polytechnic University, Hong Kong 999077, ChinaDepartment of Biomedical Engineering, The Hong Kong Polytechnic University, Hong Kong 999077, ChinaDepartment of Biomedical Engineering, The Hong Kong Polytechnic University, Hong Kong 999077, ChinaDepartment of Biomedical Engineering, The Hong Kong Polytechnic University, Hong Kong 999077, ChinaDepartment of Biomedical Engineering, The Hong Kong Polytechnic University, Hong Kong 999077, ChinaDepartment of Biomedical Engineering, The Hong Kong Polytechnic University, Hong Kong 999077, ChinaDepartment of Biomedical Engineering, The Hong Kong Polytechnic University, Hong Kong 999077, ChinaDepartment of Biomedical Engineering, The Hong Kong Polytechnic University, Hong Kong 999077, ChinaDepartment of Biomedical Engineering, The Hong Kong Polytechnic University, Hong Kong 999077, ChinaDepartment of Biomedical Engineering, The Hong Kong Polytechnic University, Hong Kong 999077, ChinaReal-time detection of fatigue in the elderly during physical exercises can help identify the stability and thus falling risks which are commonly achieved by the investigation of kinematic parameters. In this study, we aimed to identify the change in gait variability parameters from inertial measurement units (IMU) during a course of 60 min brisk walking which could lay the foundation for the development of fatigue-detecting wearable sensors. Eighteen elderly people were invited to participate in the brisk walking trials for 60 min with a single IMU attached to the posterior heel region of the dominant side. Nine sets of signals, including the accelerations, angular velocities, and rotation angles of the heel in three anatomical axes, were measured and extracted at the three walking times (baseline, 30th min, and 60th min) of the trial for analysis. Sixteen of eighteen participants reported fatigue after walking, and there were significant differences in the median acceleration (<i>p</i> = 0.001), variability of angular velocity (<i>p</i> = 0.025), and range of angle rotation (<i>p</i> = 0.0011), in the medial–lateral direction. In addition, there were also significant differences in the heel pronation angle (<i>p</i> = 0.005) and variability and energy consumption of the angles in the anterior–posterior axis (<i>p</i> = 0.028, <i>p</i> = 0.028), medial–lateral axis (<i>p</i> = 0.014, <i>p</i> = 0.014), and vertical axis (<i>p</i> = 0.002, <i>p</i> < 0.001). Our study demonstrated that a single IMU on the posterior heel of the dominant side can address the variability of kinematics parameters for elderly performing prolonged brisk walking and could serve as an indicator for walking instability, and thus fatigue.https://www.mdpi.com/1424-8220/20/23/6983fatiguebrisk walkingkinematicsgaitinertial measurement unit |
| spellingShingle | Guoxin Zhang Ivy Kwan-Kei Wong Tony Lin-Wei Chen Tommy Tung-Ho Hong Duo Wai-Chi Wong Yinghu Peng Fei Yan Yan Wang Qitao Tan Ming Zhang Identifying Fatigue Indicators Using Gait Variability Measures: A Longitudinal Study on Elderly Brisk Walking Sensors fatigue brisk walking kinematics gait inertial measurement unit |
| title | Identifying Fatigue Indicators Using Gait Variability Measures: A Longitudinal Study on Elderly Brisk Walking |
| title_full | Identifying Fatigue Indicators Using Gait Variability Measures: A Longitudinal Study on Elderly Brisk Walking |
| title_fullStr | Identifying Fatigue Indicators Using Gait Variability Measures: A Longitudinal Study on Elderly Brisk Walking |
| title_full_unstemmed | Identifying Fatigue Indicators Using Gait Variability Measures: A Longitudinal Study on Elderly Brisk Walking |
| title_short | Identifying Fatigue Indicators Using Gait Variability Measures: A Longitudinal Study on Elderly Brisk Walking |
| title_sort | identifying fatigue indicators using gait variability measures a longitudinal study on elderly brisk walking |
| topic | fatigue brisk walking kinematics gait inertial measurement unit |
| url | https://www.mdpi.com/1424-8220/20/23/6983 |
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